Businesses and consumers rely on their network service provider to provide a reliable communications infrastructure. For example, more and more businesses and consumers are relying on their Internet connections for much of their voice and data communications. However, from time to time, the network may suffer a network event that impacts the services provided to its customers, e.g., a failure or degradation of a network component. When such network event occurs, the network service provider is tasked with the responsibility for uncovering the source of the network event. In one example, the service provider may employ network personnel to analyze the detailed data associated with each event to identify the root cause. Unfortunately, a large service provider's network may experience thousands or possibly ten of thousands of network events for a given time period. As such, the process of identifying the source of all the network events is very labor intensive and may require some time before the source is properly identified.
Existing network management methods focus on the analysis of individual network events. This approach may be used for hard failures, e.g., link failures. However, some network events may have a short duration, where the symptoms of the network events may disappear by the time the network personnel can react to analyze them. For example, the network event may be a chronic network event with symptoms that keep re-appearing and disappearing. Generating alerts each time a symptom reappears creates too many alerts that may appear to be unrelated. Detecting and analyzing chronic network conditions is essentially performed by reviewing the data for multiple events reported at different times. This is a time-consuming, tedious and error-prone process. Furthermore, such process requires a significant amount of time before the source can be identified, thereby causing dissatisfaction for the customers and can potentially lead to a loss of business for the network service provider.